Job Information
New York University Postdoctoral Associate (Ho Lab | Interactive Machine Learning) in New York, New York
The Computation and Decision-Making Lab at New York University, led by Principal Investigator Mark Ho, is seeking a highly motivated and talented Postdoctoral Associate. This is an exciting opportunity for individuals with expertise and/or a strong interest in computational cognitive modeling (e.g., Bayesian models of cognition) and machine learning, particularly deep reinforcement learning methods.
Key responsibilities:
Lead cutting-edge research projects focused on developing novel interactive machine learning techniques informed by behavioral experiments with humans.
Collaborate closely with the PI, lab members, and external partners, including industry collaborators at Toyota Research Institute (TRI).
Conduct and publish high-impact research in top-tier journals and conferences.
What We Offer:
A dynamic and collaborative research environment at NYU, a leading institution in cognitive science and machine learning.
Mentorship and professional development opportunities under the guidance of PI Mark Ho.
Collaboration with the Toyota Research Institute (TRI), providing unique opportunities to work with industry leaders and apply research in real-world contexts.
Access to state-of-the-art research facilities and resources at NYU.
A supportive network and a stimulating intellectual environment at NYU, including the Department of Psychology and Center for Data Science.
Ideal starting date would be early Fall 2024, but a later start date is possible for oustanding candidates. Applications will be reviewed until the position is filled.
In compliance with NYC’s Pay Transparency Act, the annual base salary range for this position is $62,500-$90,000. New York University considers factors such as (but not limited to) the specific grant funding and the terms of the research grant when extending an offer.
Ph.D. in Cognitive Science, Computer Science, Psychology, or a related field.
Strong background in computational cognitive modeling and machine learning.
Experience with or interest in deep reinforcement learning methods.
Demonstrated ability to lead research projects and work collaboratively.
Please apply with your CV and 2-4 contact references.
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